Home  >>  Archives  >>  Volume 10 Number 4  >>  st0207

The Stata Journal
Volume 10 Number 4: pp. 507-539



Subscribe to the Stata Journal
cover

A suite of commands for fitting the skew-normal and skew-t models

Yulia V. Marchenko
StataCorp
College Station, TX
ymarchenko@stata.com
Marc G. Genton
Department of Statistics
Texas A&M University
College Station, TX
genton@stat.tamu.edu
Abstract.  Nonnormal data arise often in practice, prompting the development of flexible distributions for modeling such situations. In this article, we describe two multivariate distributions, the skew-normal and the skew-t, which can be used to model skewed and heavy-tailed continuous data. We then discuss some inferential issues that can arise when fitting these distributions to real data. We also consider the use of these distributions in a regression setting for more flexible parametric modeling of the conditional distribution given other predictors. We present commands for fitting univariate and multivariate skew-normal and skew-t regressions in Stata (skewnreg, skewtreg, mskewnreg, and mskewtreg) as well as some postestimation features (predict and skewrplot). We also demonstrate the use of the commands for the analysis of the famous Australian Institute of Sport data and U.S. precipitation data.
Terms of use     View this article (PDF)

View all articles by these authors: Yulia V. Marchenko, Marc G. Genton

View all articles with these keywords: skewnreg, skewtreg, mskewnreg, mskewtreg, skewrplot, predict, distribution, heavy tails, nonnormal, precipitation, regression, skewness, skew-normal, skew-t

Download citation: BibTeX  RIS

Download citation and abstract: BibTeX  RIS